How big data will feed the global population – however big it gets

On the MoneyWeek cruise last week there was much talk about sustainability – about pollution, about climate change, about energy usage and waste and generally about the ability of the earth to keep giving and giving to a growing human population.

Regular readers will know that, being great believers in human ingenuity, we are generally optimistic on these things. That’s a position increasingly borne out by new technology.

Consider agriculture. The truth is that, while there are obviously iffy moments (North Korea, China’s ‘great leap forward’, etc) agricultural yields always rise over time as new techniques and technologies take farming to new levels. Some of the our major crops have seen yields rise ten-fold in the last 200 years – corn yields alone are up four-fold since the 1950s.

We’re reaching one of those new levels right now thanks to ‘precision agriculture’ – a mixture of big data and (coming soon) robotics that helps farmers to customise the cultivation of every square foot of their land.

According to IBM (which is active in the area) by “collecting real-time data on weather, soil and air quality, crop maturity and even equipment and labour costs and availability” and then using predictive analytics, farmers can make smarter decisions, decisions that result in better productivity, less waste, fewer pesticides, less energy and water usage and, in the end, fewer people.

One of the best descriptions of how all this works comes from Jess Lowenberg-DeBoer in Foreign Affairs magazine. The key to getting this right is to use what is known as ‘variable rate technology’ to map every part of a field for things such as phosphates, acidity, potassium and the like, and then to treat each part of any field with the fertilisers that suits it and to see which fields will work best for which crops at which time of year.

Right now, this means putting sensors in the soil manually to check which bit needs what, something that means that, in the US, they are used only every 2.5 acres (in Brazil it is every 12). That’s a start, but it also means that “huge productivity gains” are missed – soil can change every few feet.

It’s also expensive – which is why only 20% of US farms are fully precision-farmed. However, new sensors are in development that can be put into the ground every few feet, take regular readings and report those readings via GPS, something that will lead to a system whereby each plant effectively reports its needs as the tractor approaches. Fertiliser drops can then be automatically adjusted as the vehicle moves down a field.

There are also sensors in development that can check on the colours of plants to judge their water and nitrogen requirements.

There’s more. GPS data can also be used to ‘auto-guide’ tractors. Manual driving is skilled and expensive, and involves a lot of overlapping (farmers worry more about missing bits of the field than they do about over fertilising), says Lowenberg-DeBoer. Auto-guidance takes away this problem (nothing is missed and nothing is done twice).

That takes us on to the next bit.

Some 60% of UK farms are thought to use some kind of precision farming techniques (sensor systems, cameras, drones, virtual field maps, GPS-guided tractors etc) but if tractors can be guided via GPS they don’t need drivers at all. And if tractors don’t need drivers (driverless tractors are being tested and introduced in the US), they don’t need to be particularly big.

The future might be about entirely automated agriculture – fields looked after by bots on the ground checking for weeds, pests and fertiliser levels, while drones check the weather above and report all information back to the farmer’s central systems.

There’s a fun piece on this in the Guardian. The key point to note is that this isn’t all futuristic imagining about how we might feed a future world, it is technology we have and we are beginning to use. As one farmer told the Guardian, “in ten years we will look back at today and think that we were dinosaurs in our methods”.

So how do we invest in all this? There are the big players – IBM and Accenture being the obvious players in digital agriculture, and John Deere being the obvious in the equipment area (they’ll be making the driverless tractors). Otherwise a lot of the interesting companies in the area are unlisted (the UK’s Precision Decisions for example).

Finally, we talked at length on the MoneyWeek Cruise about a French firm that has a finger in many of the relevant pies here. I will be telling John all about it in our podcast on Friday. Look out for that!